Alternatives to BigLake
Compare BigLake alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to BigLake in 2024. Compare features, ratings, user reviews, pricing, and more from BigLake competitors and alternatives in order to make an informed decision for your business.
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1
Google Cloud BigQuery
Google
BigQuery is a serverless, multicloud data warehouse that simplifies the process of working with all types of data so you can focus on getting valuable business insights quickly. At the core of Google’s data cloud, BigQuery allows you to simplify data integration, cost effectively and securely scale analytics, share rich data experiences with built-in business intelligence, and train and deploy ML models with a simple SQL interface, helping to make your organization’s operations more data-driven. -
2
KrakenD
KrakenD
KrakenD is a high-performance API Gateway optimized for resource efficiency, capable of managing 70,000 requests per second on a single instance. The stateless architecture allows for straightforward, linear scalability, eliminating the need for complex coordination or database maintenance. It supports various protocols and API specifications, with features like fine-grained access controls, data transformation, and caching. Unique to KrakenD is its ability to aggregate multiple API responses into one, streamlining client-side operations. Security-wise, KrakenD aligns with OWASP standards and doesn't store data, making compliance simpler. It offers a declarative configuration and integrates with third-party logging and metrics tools. With transparent pricing and an open-source option, KrakenD is a comprehensive API Gateway solution for organizations prioritizing performance and scalability. -
3
Amazon Redshift
Amazon
More customers pick Amazon Redshift than any other cloud data warehouse. Redshift powers analytical workloads for Fortune 500 companies, startups, and everything in between. Companies like Lyft have grown with Redshift from startups to multi-billion dollar enterprises. No other data warehouse makes it as easy to gain new insights from all your data. With Redshift you can query petabytes of structured and semi-structured data across your data warehouse, operational database, and your data lake using standard SQL. Redshift lets you easily save the results of your queries back to your S3 data lake using open formats like Apache Parquet to further analyze from other analytics services like Amazon EMR, Amazon Athena, and Amazon SageMaker. Redshift is the world’s fastest cloud data warehouse and gets faster every year. For performance intensive workloads you can use the new RA3 instances to get up to 3x the performance of any cloud data warehouse.Starting Price: $0.25 per hour -
4
Tabular
Tabular
Tabular is an open table store from the creators of Apache Iceberg. Connect multiple computing engines and frameworks. Decrease query time and storage costs by up to 50%. Centralize enforcement of data access (RBAC) policies. Connect any query engine or framework, including Athena, BigQuery, Redshift, Snowflake, Databricks, Trino, Spark, and Python. Smart compaction, clustering, and other automated data services reduce storage costs and query times by up to 50%. Unify data access at the database or table. RBAC controls are simple to manage, consistently enforced, and easy to audit. Centralize your security down to the table. Tabular is easy to use plus it features high-powered ingestion, performance, and RBAC under the hood. Tabular gives you the flexibility to work with multiple “best of breed” compute engines based on their strengths. Assign privileges at the data warehouse database, table, or column level.Starting Price: $100 per month -
5
Delta Lake
Delta Lake
Delta Lake is an open-source storage layer that brings ACID transactions to Apache Spark™ and big data workloads. Data lakes typically have multiple data pipelines reading and writing data concurrently, and data engineers have to go through a tedious process to ensure data integrity, due to the lack of transactions. Delta Lake brings ACID transactions to your data lakes. It provides serializability, the strongest level of isolation level. Learn more at Diving into Delta Lake: Unpacking the Transaction Log. In big data, even the metadata itself can be "big data". Delta Lake treats metadata just like data, leveraging Spark's distributed processing power to handle all its metadata. As a result, Delta Lake can handle petabyte-scale tables with billions of partitions and files at ease. Delta Lake provides snapshots of data enabling developers to access and revert to earlier versions of data for audits, rollbacks or to reproduce experiments. -
6
AWS Lake Formation
Amazon
AWS Lake Formation is a service that makes it easy to set up a secure data lake in days. A data lake is a centralized, curated, and secured repository that stores all your data, both in its original form and prepared for analysis. A data lake lets you break down data silos and combine different types of analytics to gain insights and guide better business decisions. Setting up and managing data lakes today involves a lot of manual, complicated, and time-consuming tasks. This work includes loading data from diverse sources, monitoring those data flows, setting up partitions, turning on encryption and managing keys, defining transformation jobs and monitoring their operation, reorganizing data into a columnar format, deduplicating redundant data, and matching linked records. Once data has been loaded into the data lake, you need to grant fine-grained access to datasets, and audit access over time across a wide range of analytics and machine learning (ML) tools and services. -
7
lakeFS
Treeverse
lakeFS enables you to manage your data lake the way you manage your code. Run parallel pipelines for experimentation and CI/CD for your data. Simplifying the lives of engineers, data scientists and analysts who are transforming the world with data. lakeFS is an open source platform that delivers resilience and manageability to object-storage based data lakes. With lakeFS you can build repeatable, atomic and versioned data lake operations, from complex ETL jobs to data science and analytics. lakeFS supports AWS S3, Azure Blob Storage and Google Cloud Storage (GCS) as its underlying storage service. It is API compatible with S3 and works seamlessly with all modern data frameworks such as Spark, Hive, AWS Athena, Presto, etc. lakeFS provides a Git-like branching and committing model that scales to exabytes of data by utilizing S3, GCS, or Azure Blob for storage. -
8
Aserto
Aserto
Aserto helps developers build secure applications. It makes it easy to add fine-grained, policy-based, real-time access control to your applications and APIs. Aserto handles all the heavy lifting required to achieve secure, scalable, high-performance access management. It offers blazing-fast authorization of a local library coupled with a centralized control plane for managing policies, user attributes, relationship data, and decision logs. And it comes with everything you need to implement RBAC or fine-grained authorization models, such as ABAC, and ReBAC. Take a look at our open-source projects: - Topaz.sh: a standalone authorizer you can deploy in your environment to add fine-grained access control to your applications. Topaz lets you combine OPA policies with Zanzibar’s data model for complete flexibility. - OpenPolicyContainers.com (OPCR) secures OPA policies across the lifecycle by adding the ability to tag, verStarting Price: $0 -
9
IBM watsonx.data
IBM
Put your data to work, wherever it resides, with the open, hybrid data lakehouse for AI and analytics. Connect your data from anywhere, in any format, and access through a single point of entry with a shared metadata layer. Optimize workloads for price and performance by pairing the right workloads with the right query engine. Embed natural-language semantic search without the need for SQL, so you can unlock generative AI insights faster. Manage and prepare trusted data to improve the relevance and precision of your AI applications. Use all your data, everywhere. With the speed of a data warehouse, the flexibility of a data lake, and special features to support AI, watsonx.data can help you scale AI and analytics across your business. Choose the right engines for your workloads. Flexibly manage cost, performance, and capability with access to multiple open engines including Presto, Presto C++, Spark Milvus, and more. -
10
Onehouse
Onehouse
The only fully managed cloud data lakehouse designed to ingest from all your data sources in minutes and support all your query engines at scale, for a fraction of the cost. Ingest from databases and event streams at TB-scale in near real-time, with the simplicity of fully managed pipelines. Query your data with any engine, and support all your use cases including BI, real-time analytics, and AI/ML. Cut your costs by 50% or more compared to cloud data warehouses and ETL tools with simple usage-based pricing. Deploy in minutes without engineering overhead with a fully managed, highly optimized cloud service. Unify your data in a single source of truth and eliminate the need to copy data across data warehouses and lakes. Use the right table format for the job, with omnidirectional interoperability between Apache Hudi, Apache Iceberg, and Delta Lake. Quickly configure managed pipelines for database CDC and streaming ingestion. -
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Serverless, interactive querying for analyzing data in IBM Cloud Object Storage. Query your data directly where it is stored, there's no ETL, no databases, and no infrastructure to manage. IBM Cloud SQL Query uses Apache Spark, an open-source, fast, extensible, in-memory data processing engine optimized for low latency and ad hoc analysis of data. No ETL or schema definition needed to enable SQL queries. Analyze data where it sits in IBM Cloud Object Storage using our query editor and REST API. Run as many queries as you need; with pay-per-query pricing, you pay only for the data scan. Compress or partition data to drive savings and performance. IBM Cloud SQL Query is highly available and executes queries using compute resources across multiple facilities. IBM Cloud SQL Query supports a variety of data formats such as CSV, JSON and Parquet, and allows for standard ANSI SQL.Starting Price: $5.00/Terabyte-Month
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12
Tokern
Tokern
Open source data governance suite for databases and data lakes. Tokern is a simple to use toolkit to collect, organize and analyze data lake's metadata. Run as a command-line app for quick tasks. Run as a service for continuous collection of metadata. Analyze lineage, access control and PII datasets using reporting dashboards or programmatically in Jupyter notebooks. Tokern is an open source data governance suite for databases and data lakes. Improve ROI of your data, comply with regulations like HIPAA, CCPA and GDPR and protect critical data from insider threats with confidence. Centralized metadata management of users, datasets and jobs. Powers other data governance features. Track Column Level Data Lineage for Snowflake, AWS Redshift and BigQuery. Build lineage from query history or ETL scripts. Explore lineage using interactive graphs or programmatically using APIs or SDKs. -
13
SecuPi
SecuPi
SecuPi provides an overarching data-centric security platform, delivering fine-grained access control (ABAC), Database Activity Monitoring (DAM) and de-identification using FPE encryption, physical and dynamic masking and deletion (RTBF). SecuPi offers wide coverage across packaged and home-grown applications, direct access tools, big data, and cloud environments. One data security platform for monitoring, controlling, encrypting, and classifying data across all cloud & on-prem platforms seamlessly with no code changes. Agile and efficient configurable platform to meet current & future regulatory and audit requirements. No source-code changes with fast & cost-efficient implementation. SecuPi’s fine-grain data access controls protect sensitive data so users get access only to data they are entitled to view, and no more. Seamlessly integrate with Starburst/Trino for automated enforcement of data access policies and data protection operations. -
14
Electrik.Ai
Electrik.Ai
Automatically ingest marketing data into any data warehouse or cloud file storage of your choice such as BigQuery, Snowflake, Redshift, Azure SQL, AWS S3, Azure Data Lake, Google Cloud Storage with our fully managed ETL pipelines in the cloud. Our hosted marketing data warehouse integrates all your marketing data and provides ad insights, cross-channel attribution, content insights, competitor Insights, and more. Our customer data platform performs identity resolution in real-time across data sources thus enabling a unified view of the customer and their journey. Electrik.AI is a cloud-based marketing analytics software and full-service platform. Electrik.AI’s Google Analytics Hit Data Extractor enriches and extracts the un-sampled hit level data sent to Google Analytics from the website or application and periodically ships it to your desired destination database/data warehouse or file/data lake.Starting Price: $49 per month -
15
Imply
Imply
Imply is a real-time analytics platform built on Apache Druid, designed to handle large-scale, high-performance OLAP (Online Analytical Processing) workloads. It offers real-time data ingestion, fast query performance, and the ability to perform complex analytical queries on massive datasets with low latency. Imply is tailored for organizations that need interactive analytics, real-time dashboards, and data-driven decision-making at scale. It provides a user-friendly interface for data exploration, along with advanced features such as multi-tenancy, fine-grained access controls, and operational insights. With its distributed architecture and scalability, Imply is well-suited for use cases in streaming data analytics, business intelligence, and real-time monitoring across industries. -
16
Upsolver
Upsolver
Upsolver makes it incredibly simple to build a governed data lake and to manage, integrate and prepare streaming data for analysis. Define pipelines using only SQL on auto-generated schema-on-read. Easy visual IDE to accelerate building pipelines. Add Upserts and Deletes to data lake tables. Blend streaming and large-scale batch data. Automated schema evolution and reprocessing from previous state. Automatic orchestration of pipelines (no DAGs). Fully-managed execution at scale. Strong consistency guarantee over object storage. Near-zero maintenance overhead for analytics-ready data. Built-in hygiene for data lake tables including columnar formats, partitioning, compaction and vacuuming. 100,000 events per second (billions daily) at low cost. Continuous lock-free compaction to avoid “small files” problem. Parquet-based tables for fast queries. -
17
Apache Iceberg
Apache Software Foundation
Iceberg is a high-performance format for huge analytic tables. Iceberg brings the reliability and simplicity of SQL tables to big data, while making it possible for engines like Spark, Trino, Flink, Presto, Hive and Impala to safely work with the same tables, at the same time. Iceberg supports flexible SQL commands to merge new data, update existing rows, and perform targeted deletes. Iceberg can eagerly rewrite data files for read performance, or it can use delete deltas for faster updates. Iceberg handles the tedious and error-prone task of producing partition values for rows in a table and skips unnecessary partitions and files automatically. No extra filters are needed for fast queries, and the table layout can be updated as data or queries change.Starting Price: Free -
18
VeloDB
VeloDB
Powered by Apache Doris, VeloDB is a modern data warehouse for lightning-fast analytics on real-time data at scale. Push-based micro-batch and pull-based streaming data ingestion within seconds. Storage engine with real-time upsert、append and pre-aggregation. Unparalleled performance in both real-time data serving and interactive ad-hoc queries. Not just structured but also semi-structured data. Not just real-time analytics but also batch processing. Not just run queries against internal data but also work as a federate query engine to access external data lakes and databases. Distributed design to support linear scalability. Whether on-premise deployment or cloud service, separation or integration of storage and compute, resource usage can be flexibly and efficiently adjusted according to workload requirements. Built on and fully compatible with open source Apache Doris. Support MySQL protocol, functions, and SQL for easy integration with other data tools. -
19
Google Cloud Data Fusion
Google
Open core, delivering hybrid and multi-cloud integration. Data Fusion is built using open source project CDAP, and this open core ensures data pipeline portability for users. CDAP’s broad integration with on-premises and public cloud platforms gives Cloud Data Fusion users the ability to break down silos and deliver insights that were previously inaccessible. Integrated with Google’s industry-leading big data tools. Data Fusion’s integration with Google Cloud simplifies data security and ensures data is immediately available for analysis. Whether you’re curating a data lake with Cloud Storage and Dataproc, moving data into BigQuery for data warehousing, or transforming data to land it in a relational store like Cloud Spanner, Cloud Data Fusion’s integration makes development and iteration fast and easy. -
20
Trino
Trino
Trino is a query engine that runs at ludicrous speed. Fast-distributed SQL query engine for big data analytics that helps you explore your data universe. Trino is a highly parallel and distributed query engine, that is built from the ground up for efficient, low-latency analytics. The largest organizations in the world use Trino to query exabyte-scale data lakes and massive data warehouses alike. Supports diverse use cases, ad-hoc analytics at interactive speeds, massive multi-hour batch queries, and high-volume apps that perform sub-second queries. Trino is an ANSI SQL-compliant query engine, that works with BI tools such as R, Tableau, Power BI, Superset, and many others. You can natively query data in Hadoop, S3, Cassandra, MySQL, and many others, without the need for complex, slow, and error-prone processes for copying the data. Access data from multiple systems within a single query.Starting Price: Free -
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Apache Doris
The Apache Software Foundation
Apache Doris is a modern data warehouse for real-time analytics. It delivers lightning-fast analytics on real-time data at scale. Push-based micro-batch and pull-based streaming data ingestion within a second. Storage engine with real-time upsert, append and pre-aggregation. Optimize for high-concurrency and high-throughput queries with columnar storage engine, MPP architecture, cost based query optimizer, vectorized execution engine. Federated querying of data lakes such as Hive, Iceberg and Hudi, and databases such as MySQL and PostgreSQL. Compound data types such as Array, Map and JSON. Variant data type to support auto data type inference of JSON data. NGram bloomfilter and inverted index for text searches. Distributed design for linear scalability. Workload isolation and tiered storage for efficient resource management. Supports shared-nothing clusters as well as separation of storage and compute.Starting Price: Free -
22
SelectDB
SelectDB
SelectDB is a modern data warehouse based on Apache Doris, which supports rapid query analysis on large-scale real-time data. From Clickhouse to Apache Doris, to achieve the separation of the lake warehouse and upgrade to the lake warehouse. The fast-hand OLAP system carries nearly 1 billion query requests every day to provide data services for multiple scenes. Due to the problems of storage redundancy, resource seizure, complicated governance, and difficulty in querying and adjustment, the original lake warehouse separation architecture was decided to introduce Apache Doris lake warehouse, combined with Doris's materialized view rewriting ability and automated services, to achieve high-performance data query and flexible data governance. Write real-time data in seconds, and synchronize flow data from databases and data streams. Data storage engine for real-time update, real-time addition, and real-time pre-polymerization.Starting Price: $0.22 per hour -
23
Tencent Cloud Message Queue
Tencent
CMQ can efficiently send/receive and push tens of millions of messages and retain an unlimited number of messages. It features an extremely high throughput and can process over 100,000 queries per second (QPS) with one single cluster, fully meeting the messaging needs of your businesses. When each message is returned to the user, CMQ writes three copies of the message data to different physical servers so that when one of the servers fails, the backend data replication mechanism can quickly migrate the data. CMQ supports HTTPS-based secure access and utilizes Tencent Cloud's multi-dimensional security protection to defend against network attacks and protect the privacy of your businesses. Plus, it supports managing master/sub-accounts and collaborator accounts for fine-grained resource access control. -
24
Amazon EMR
Amazon
Amazon EMR is the industry-leading cloud big data platform for processing vast amounts of data using open-source tools such as Apache Spark, Apache Hive, Apache HBase, Apache Flink, Apache Hudi, and Presto. With EMR you can run Petabyte-scale analysis at less than half of the cost of traditional on-premises solutions and over 3x faster than standard Apache Spark. For short-running jobs, you can spin up and spin down clusters and pay per second for the instances used. For long-running workloads, you can create highly available clusters that automatically scale to meet demand. If you have existing on-premises deployments of open-source tools such as Apache Spark and Apache Hive, you can also run EMR clusters on AWS Outposts. Analyze data using open-source ML frameworks such as Apache Spark MLlib, TensorFlow, and Apache MXNet. Connect to Amazon SageMaker Studio for large-scale model training, analysis, and reporting. -
25
OpenDocMan
OpenDocMan
OpenDocMan is a free, web-based, open-source document management system (DMS) written in PHP and designed to comply with ISO 17025 and OIE standards for document management. It features web-based access, fine-grained control of access to files, and automated install and upgrades. OpenDocMan was developed under the open-source GPL license, which in a nutshell allows you to use the program for free and modify it any way you wish. We also encourage feedback from our users when they encounter issues, or have suggestions. Free document management software is good for you. IT staff and managers can delegate document management duties to any number of staff members, through user and group permissions. Permissions can be set as restrictively or permissively as needed. -
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Dylan
Dylan
It is dynamic while providing a programming model designed to support efficient machine code generation, including fine-grained control over dynamic and static behaviors. Describes the Open Dylan implementation of the Dylan language, a core set of Dylan libraries, and a library interchange mechanism. The core libraries provide many language extensions, a threads interface, and object finalization, printing and output formatting modules, a streams module, a sockets module, and modules providing an interface to operating system features such as the file system, time and date information, the host machine environment, as well as a foreign function interface and some low-level access to the Microsoft Win32 API.Starting Price: Free -
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Apache Ranger
The Apache Software Foundation
Apache Ranger™ is a framework to enable, monitor and manage comprehensive data security across the Hadoop platform. The vision with Ranger is to provide comprehensive security across the Apache Hadoop ecosystem. With the advent of Apache YARN, the Hadoop platform can now support a true data lake architecture. Enterprises can potentially run multiple workloads, in a multi tenant environment. Data security within Hadoop needs to evolve to support multiple use cases for data access, while also providing a framework for central administration of security policies and monitoring of user access. Centralized security administration to manage all security related tasks in a central UI or using REST APIs. Fine grained authorization to do a specific action and/or operation with Hadoop component/tool and managed through a central administration tool. Standardize authorization method across all Hadoop components. Enhanced support for different authorization methods - Role based access control etc. -
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Dremio
Dremio
Dremio delivers lightning-fast queries and a self-service semantic layer directly on your data lake storage. No moving data to proprietary data warehouses, no cubes, no aggregation tables or extracts. Just flexibility and control for data architects, and self-service for data consumers. Dremio technologies like Data Reflections, Columnar Cloud Cache (C3) and Predictive Pipelining work alongside Apache Arrow to make queries on your data lake storage very, very fast. An abstraction layer enables IT to apply security and business meaning, while enabling analysts and data scientists to explore data and derive new virtual datasets. Dremio’s semantic layer is an integrated, searchable catalog that indexes all of your metadata, so business users can easily make sense of your data. Virtual datasets and spaces make up the semantic layer, and are all indexed and searchable. -
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Y42
Datos-Intelligence GmbH
Y42 is the first fully managed Modern DataOps Cloud. It is purpose-built to help companies easily design production-ready data pipelines on top of their Google BigQuery or Snowflake cloud data warehouse. Y42 provides native integration of best-of-breed open-source data tools, comprehensive data governance, and better collaboration for data teams. With Y42, organizations enjoy increased accessibility to data and can make data-driven decisions quickly and efficiently. -
30
ReByte
RealChar.ai
Action-based orchestration to build complex backend agents with multiple steps. Working for all LLMs, build fully customized UI for your agent without writing a single line of code, serving on your domain. Track every step of your agent, literally every step, to deal with the nondeterministic nature of LLMs. Build fine-grain access control over your application, data, and agent. Specialized fine-tuned model for accelerating software development. Automatically handle concurrency, rate limiting, and more.Starting Price: $10 per month -
31
Alibaba Cloud Drive
Alibaba Cloud
Alibaba Cloud Photo and Drive Service (PDS) enables you to build a cloud drive and provide it to your customers with enterprise-level features, such as large-volume file storage, ultra-fast file sharing, file and directory management, fine-grained access and permission control, and AI file analysis and classification. Enjoy super-fast speed when storing, sharing, and downloading files with Alibaba Cloud Drive’s centralized storage of metadata and global accelerated networking. Extract, recognize, and re-categorize file metadata and support massive data queries based on Alibaba Cloud’s AI capabilities to understand unstructured data. Ensure data security with server-side data encryption, HTTPS 2.0-based transmission, end-to-end data validation, flexible authorization methods, and file watermarking functions. -
32
Qubole
Qubole
Qubole is a simple, open, and secure Data Lake Platform for machine learning, streaming, and ad-hoc analytics. Our platform provides end-to-end services that reduce the time and effort required to run Data pipelines, Streaming Analytics, and Machine Learning workloads on any cloud. No other platform offers the openness and data workload flexibility of Qubole while lowering cloud data lake costs by over 50 percent. Qubole delivers faster access to petabytes of secure, reliable and trusted datasets of structured and unstructured data for Analytics and Machine Learning. Users conduct ETL, analytics, and AI/ML workloads efficiently in end-to-end fashion across best-of-breed open source engines, multiple formats, libraries, and languages adapted to data volume, variety, SLAs and organizational policies. -
33
OpenReplay
OpenReplay
Open-source session replay suite, built for developers and self-hosted for full control over your data. Understand every issue, as if it happened in your own browser. Look under the hood, while watching your users. Everything developers need to fix what's broken. One platform to replay sessions, understand issues, monitor your web app, and assist your customers. Relive your user's experience. Feel their struggle, uncover hidden issues and build stellar experiences. A full-featured session replay suite you can self-host, so your customer data never leaves your infrastructure. No more sharing of your data with 3rd parties. Have full control over what's captured. Stop wasting time on lengthy compliance and security checks. Fine-grained privacy features for sanitizing user data. Host your session replay tool yourself and stop sending data to third parties. Not a big fan of self-deployments? Use our cloud and get started in minutes.Starting Price: $3.95 per month -
34
Jmix
Haulmont Technology
Discover a rapid application development platform that supercharges your digital initiatives without low-code limitations, vendor dependency, and usage-based fees. Jmix general purpose open architecture based on a future-proof technology stack is capable to support various digital initiatives across the organization. Jmix applications are indeed yours and can be supported independently thanks to open-source runtime utilizing mainstream technologies. Your data is secure with a server-side frontend development model and fine-grained access control. Any Java or Kotlin developer is a full-stack Jmix developer - you don’t need separate backend and frontend teams. Visual tools help onboard developers who have little experience or move from an obsolete stack. Jmix’s data-centric approach and single development language make it a natural fit to migrate legacy applications. Jmix supercharges your team with high-productivity tools and ready-to-use components.Starting Price: $45 per month -
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Deep Lake
activeloop
Generative AI may be new, but we've been building for this day for the past 5 years. Deep Lake thus combines the power of both data lakes and vector databases to build and fine-tune enterprise-grade, LLM-based solutions, and iteratively improve them over time. Vector search does not resolve retrieval. To solve it, you need a serverless query for multi-modal data, including embeddings or metadata. Filter, search, & more from the cloud or your laptop. Visualize and understand your data, as well as the embeddings. Track & compare versions over time to improve your data & your model. Competitive businesses are not built on OpenAI APIs. Fine-tune your LLMs on your data. Efficiently stream data from remote storage to the GPUs as models are trained. Deep Lake datasets are visualized right in your browser or Jupyter Notebook. Instantly retrieve different versions of your data, materialize new datasets via queries on the fly, and stream them to PyTorch or TensorFlow.Starting Price: $995 per month -
36
Amazon MSK
Amazon
Amazon MSK is a fully managed service that makes it easy for you to build and run applications that use Apache Kafka to process streaming data. Apache Kafka is an open-source platform for building real-time streaming data pipelines and applications. With Amazon MSK, you can use native Apache Kafka APIs to populate data lakes, stream changes to and from databases, and power machine learning and analytics applications. Apache Kafka clusters are challenging to setup, scale, and manage in production. When you run Apache Kafka on your own, you need to provision servers, configure Apache Kafka manually, replace servers when they fail, orchestrate server patches and upgrades, architect the cluster for high availability, ensure data is durably stored and secured, setup monitoring and alarms, and carefully plan scaling events to support load changes.Starting Price: $0.0543 per hour -
37
doolytic
doolytic
doolytic is leading the way in big data discovery, the convergence of data discovery, advanced analytics, and big data. doolytic is rallying expert BI users to the revolution in self-service exploration of big data, revealing the data scientist in all of us. doolytic is an enterprise software solution for native discovery on big data. doolytic is based on best-of-breed, scalable, open-source technologies. Lightening performance on billions of records and petabytes of data. Structured, unstructured and real-time data from any source. Sophisticated advanced query capabilities for expert users, Integration with R for advanced and predictive applications. Search, analyze, and visualize data from any format, any source in real-time with the flexibility of Elastic. Leverage the power of Hadoop data lakes with no latency and concurrency issues. doolytic solves common BI problems and enables big data discovery without clumsy and inefficient workarounds. -
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Apache Impala
Apache
Impala provides low latency and high concurrency for BI/analytic queries on the Hadoop ecosystem, including Iceberg, open data formats, and most cloud storage options. Impala also scales linearly, even in multitenant environments. Impala is integrated with native Hadoop security and Kerberos for authentication, and via the Ranger module, you can ensure that the right users and applications are authorized for the right data. Utilize the same file and data formats and metadata, security, and resource management frameworks as your Hadoop deployment, with no redundant infrastructure or data conversion/duplication. For Apache Hive users, Impala utilizes the same metadata and ODBC driver. Like Hive, Impala supports SQL, so you don't have to worry about reinventing the implementation wheel. With Impala, more users, whether using SQL queries or BI applications, can interact with more data through a single repository and metadata stored from source through analysis.Starting Price: Free -
39
Alluxio
Alluxio
Alluxio is world’s first open source data orchestration technology for analytics and AI for the cloud. It bridges the gap between data driven applications and storage systems, bringing data from the storage tier closer to the data driven applications and makes it easily accessible enabling applications to connect to numerous storage systems through a common interface. Alluxio’s memory-first tiered architecture enables data access at speeds orders of magnitude faster than existing solutions. Imagine as an IT leader having the flexibility to choose any services that are available in public cloud and on premises. And imagine being able to scale your storage for your data lakes with control over data locality and protection for your organization. With these goals in mind, NetApp and Alluxio are joining forces to help our customers adapt to new requirements for modernizing data architecture with low-touch operations for analytics, machine learning, and artificial intelligence workflows.Starting Price: 26¢ Per SW Instance Per Hour -
40
Red Hat Quay
Red Hat
Red Hat® Quay container image registry provides storage and enables you to build, distribute, and deploy containers. Gain more security over your image repositories with automation, authentication, and authorization systems. Quay is available with OpenShift or as a standalone component. Control access of the registry with multiple identity and authentication providers (including support for teams and organization mapping). Use a fine-grained permissions system to map to your organizational structure. Transport layer security encryption helps you transit between Quay.io and your servers automatically. Integrate with vulnerability detectors (like Clair) to automatically scan your container images. Notifications alert you to known vulnerabilities. Streamline your continuous integration/continuous delivery (CI/CD) pipeline with build triggers, git hooks, and robot accounts. Audit your CI pipeline by tracking API and UI actions. -
41
The ARCON | Endpoint Privilege Management solution (EPM) grants endpoint privileges ‘just-in-time’ or ‘on-demand’ and monitors all end users for you. The tool detects insider threats, compromised identities, and other malicious attempts to breach endpoints. It has a powerful User behavior Analytics component that takes note of the normal conduct of end users and identifies atypical behavior profiles and other entities in the network. A single governance framework enables you to blacklist malicious applications, prevent data being copied from devices to removable storage, and offers fine-grained access to all applications with ‘just-in-time’ privilege elevation and demotion capabilities. No matter how many endpoints you have because of WFH and remote access workplaces, secure them all with a single endpoint management tool. Elevate privileges according to your discretion, at your convenience.
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Apache Spark
Apache Software Foundation
Apache Spark™ is a unified analytics engine for large-scale data processing. Apache Spark achieves high performance for both batch and streaming data, using a state-of-the-art DAG scheduler, a query optimizer, and a physical execution engine. Spark offers over 80 high-level operators that make it easy to build parallel apps. And you can use it interactively from the Scala, Python, R, and SQL shells. Spark powers a stack of libraries including SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming. You can combine these libraries seamlessly in the same application. Spark runs on Hadoop, Apache Mesos, Kubernetes, standalone, or in the cloud. It can access diverse data sources. You can run Spark using its standalone cluster mode, on EC2, on Hadoop YARN, on Mesos, or on Kubernetes. Access data in HDFS, Alluxio, Apache Cassandra, Apache HBase, Apache Hive, and hundreds of other data sources. -
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ELCA Smart Data Lake Builder
ELCA Group
Classical Data Lakes are often reduced to basic but cheap raw data storage, neglecting significant aspects like transformation, data quality and security. These topics are left to data scientists, who end up spending up to 80% of their time acquiring, understanding and cleaning data before they can start using their core competencies. In addition, classical Data Lakes are often implemented by separate departments using different standards and tools, which makes it harder to implement comprehensive analytical use cases. Smart Data Lakes solve these various issues by providing architectural and methodical guidelines, together with an efficient tool to build a strong high-quality data foundation. Smart Data Lakes are at the core of any modern analytics platform. Their structure easily integrates prevalent Data Science tools and open source technologies, as well as AI and ML. Their storage is cheap and scalable, supporting both unstructured data and complex data structures.Starting Price: Free -
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IBM Analytics for Apache Spark is a flexible and integrated Spark service that empowers data science professionals to ask bigger, tougher questions, and deliver business value faster. It’s an easy-to-use, always-on managed service with no long-term commitment or risk, so you can begin exploring right away. Access the power of Apache Spark with no lock-in, backed by IBM’s open-source commitment and decades of enterprise experience. A managed Spark service with Notebooks as a connector means coding and analytics are easier and faster, so you can spend more of your time on delivery and innovation. A managed Apache Spark services gives you easy access to the power of built-in machine learning libraries without the headaches, time and risk associated with managing a Sparkcluster independently.
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GeoSpock
GeoSpock
GeoSpock enables data fusion for the connected world with GeoSpock DB – the space-time analytics database. GeoSpock DB is a unique, cloud-native database optimised for querying for real-world use cases, able to fuse multiple sources of Internet of Things (IoT) data together to unlock its full value, whilst simultaneously reducing complexity and cost. GeoSpock DB enables efficient storage, data fusion, and rapid programmatic access to data, and allows you to run ANSI SQL queries and connect to analytics tools via JDBC/ODBC connectors. Users are able to perform analysis and share insights using familiar toolsets, with support for common BI tools (such as Tableau™, Amazon QuickSight™, and Microsoft Power BI™), and Data Science and Machine Learning environments (including Python Notebooks and Apache Spark). The database can also be integrated with internal applications and web services – with compatibility for open-source and visualisation libraries such as Kepler and Cesium.js. -
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Archon Data Store
Platform 3 Solutions
Archon Data Store™ is a powerful and secure open-source based archive lakehouse platform designed to store, manage, and provide insights from massive volumes of data. With its compliance features and minimal footprint, it enables large-scale search, processing, and analysis of structured, unstructured, & semi-structured data across your organization. Archon Data Store combines the best features of data warehouses and data lakes into a single, simplified platform. This unified approach eliminates data silos, streamlining data engineering, analytics, data science, and machine learning workflows. Through metadata centralization, optimized data storage, and distributed computing, Archon Data Store maintains data integrity. Its common approach to data management, security, and governance helps you operate more efficiently and innovate faster. Archon Data Store provides a single platform for archiving and analyzing all your organization's data while delivering operational efficiencies. -
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Apache Hive
Apache Software Foundation
The Apache Hive data warehouse software facilitates reading, writing, and managing large datasets residing in distributed storage using SQL. Structure can be projected onto data already in storage. A command line tool and JDBC driver are provided to connect users to Hive. Apache Hive is an open source project run by volunteers at the Apache Software Foundation. Previously it was a subproject of Apache® Hadoop®, but has now graduated to become a top-level project of its own. We encourage you to learn about the project and contribute your expertise. Traditional SQL queries must be implemented in the MapReduce Java API to execute SQL applications and queries over distributed data. Hive provides the necessary SQL abstraction to integrate SQL-like queries (HiveQL) into the underlying Java without the need to implement queries in the low-level Java API. -
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Epsilla
Epsilla
Manages the entire lifecycle of LLM application development, testing, deployment, and operation without the need to piece together multiple systems. Achieving the lowest total cost of ownership (TCO). Featuring the vector database and search engine that outperforms all other leading vendors with 10X lower query latency, 5X higher query throughput, and 3X lower cost. An innovative data and knowledge foundation that efficiently manages large-scale, multi-modality unstructured and structured data. Never have to worry about outdated information. Plug and play with state-of-the-art advanced, modular, agentic RAG and GraphRAG techniques without writing plumbing code. With CI/CD-style evaluations, you can confidently make configuration changes to your AI applications without worrying about regressions. Accelerate your iterations and move to production in days, not months. Fine-grained, role-based, and privilege-based access control.Starting Price: $29 per month -
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VMware Cloud Director
Broadcom
VMware Cloud Director is a leading cloud service-delivery platform used by some of the world’s most popular cloud providers to operate and manage successful cloud-service businesses. Using VMware Cloud Director, cloud providers deliver secure, efficient, and elastic cloud resources to thousands of enterprises and IT teams across the world. Use VMware in the cloud through one of our Cloud Provider Partners and build with VMware Cloud Director. A policy-driven approach helps ensure enterprises have isolated virtual resources, independent role-based authentication, and fine-grained control. A policy-driven approach to compute, storage, networking and security ensures tenants have securely isolated virtual resources, independent role-based authentication, and fine-grained control of their public cloud services. Stretch data centers across sites and geographies; monitor resources from an intuitive single-pane of glass with multi-site aggregate views. -
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Starburst Enterprise
Starburst Data
Starburst helps you make better decisions with fast access to all your data; Without the complexity of data movement and copies. Your company has more data than ever before, but your data teams are stuck waiting to analyze it. Starburst unlocks access to data where it lives, no data movement required, giving your teams fast & accurate access to more data for analysis. Starburst Enterprise is a fully supported, production-tested and enterprise-grade distribution of open source Trino (formerly Presto® SQL). It improves performance and security while making it easy to deploy, connect, and manage your Trino environment. Through connecting to any source of data – whether it’s located on-premise, in the cloud, or across a hybrid cloud environment – Starburst lets your team use the analytics tools they already know & love while accessing data that lives anywhere.
